Cypher Neural Network

This project implements a Cypher Neural Network using PyTorch and PyTorch Lightning. It serves as a demonstration of building, training, and deploying a neural network model for various tasks.

Project Structure

cypher-neural-network
├── src
│   ├── main.py         # Entry point for the application
│   ├── model.py        # Defines the neural network architecture
│   ├── data.py         # Handles data loading and preprocessing
│   └── train.py        # Contains the training loop for the model
├── Dockerfile           # Instructions to build the Docker image
├── requirements.txt     # Lists the Python dependencies
└── README.md            # Documentation for the project

Setup Instructions

1. Clone the repository:

   git clone <repository-url>
   cd cypher-neural-network

2. Install dependencies: It is recommended to use a virtual environment. You can create one using venv or conda.

   pip install -r requirements.txt

3. Build the Docker image: If you prefer to run the project in a Docker container, build the image using the provided Dockerfile.

   docker build -t cypher-neural-network .

4. Run the application: You can run the application using the following command:

   python src/main.py

Usage

The main entry point of the application is src/main.py, which initializes the training process. You can modify the parameters in this file to customize the training process.

License

This project is licensed under the MIT License. See the LICENSE file for more details.